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A hybrid genetic algorithm for a variant of two-dimensional packing problem
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents
Montreal, Québec, Canada
SESSION: Track 4: combinatorial optimization and metaheuristics table of contents
Pages 287-292  
Year of Publication: 2009
ISBN:978-1-60558-325-9
Authors
Jin Kim  Seoul National University, Seoul, South Korea
Byung-Ro Moon  Seoul National University, Seoul, South Korea
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

A variant of two-dimensional packing problem was given in the GECCO'2008 competition. This paper describes the genetic algorithm that produced the best result and thus won the No. 1 prize. As the problem is naturally represented by a two-dimensional chromosome, two-dimensional crossovers are used to generate more diverse chromosomes and effectively maintain geographical linkage among genes. We developed a local search heuristic based on the breadth-first search algorithm; we describe how to implement the heuristic efficiently using problem-specific knowledge. The local search was combined with a steady-state genetic algorithm and the combination showed strong synergy.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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B.-R. Moon, Y.-S. Lee, and C.-K. Kim. GEORG: VLSI circuit partitioner with a new genetic algorithm framework. Journal of Intelligent Manufacturing, 9(5):401--412, 1998.
 
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